In subterranean coal seam gas (CSG) reservoirs, massive amounts of small-sized coal fines are released during the production and development stages, especially during hydraulic fracturing stimulation. These coal fines inevitably cause mechanical pump failure and permeability damage due to aggregation and subsequent pore-throat blockage. This aggregation behavior is thus of key importance in CSG production and needs to be minimized. Consequently, such coal fines dispersions need to be stabilized, which can be achieved by the formulation of improved fracturing fluids. Here, we thus systematically investigated the effectiveness of two additives (ethanol, 0.5 wt % and SDBS, 0.001 and 0.01 wt %) on dispersion stability for a wide range of condit

The influence of the reaction gas composition during the DC magnetron sputtering process on the structural, chemical and optical properties of Ce-oxide thin films was investigated. X-ray diffraction (XRD) studies confirmed that all thin films exhibited a polycrystalline character with cubic fluorite structure for cerium dioxide. X-ray photoelectron spectroscopy (XPS) analyses revealed that cerium is present in two oxidation states, namely as CeO2 and Ce2O3, at the surface of the films prepared at oxygen/argon flow ratios between 0% and 7%, whereas the films are completely oxidized into CeO2 as the aforementioned ratio increases beyond 14%. Various optical parameters for the thin films (including an optical band gap in the range of 2.25–3.

A hydroponic experiment was carried out at the College of Agricultural Engineering Sciences - University of Baghdad during the fall season of 2019-2020 in order to improve the quality traits of broccoli grown hydroponically under the modified Nutrient Film Technique (NFT), using an internationally approved standard solution and alternative solution, the plant was enriched with ozone and the foliar application of organic nutrients. The Hydroponic study included two experiments with the standard solution (Cooper's solution) and the alternative solution (ABEER). Both experiments were implemented within the Nested Design with three replications, and both included the gas type in the main plot, which were oxygen and ozone, while the sub-

The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an